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Innovation Management – Knowledge Management Univ.-Prof. Dr.-Ing. Wolfgang Maass Chair in Economics – Information and Service Systems (ISS) Saarland University, Saarbrücken, Germany SS 2012 Wednesdays, 10:00 – 12:00 a.m. Room 0.21, B4 1

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Innovation Management – Knowledge Management Univ.-Prof. Dr.-Ing. Wolfgang Maass Chair in Economics – Information and Service Systems (ISS) Saarland University, Saarbrücken, Germany SS 2012 Wednesdays, 10:00 – 12:00 a.m. Room 0.21, B4 1

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 2  

Lecture Agenda

Innovation Management 1.  Introduction 2.  Knowledge Management 3.  Strategic Innovation Management 4.  Guest Lecture 5.  New Product Development 6.  Creativity Techniques 7.  Planning Product Features 8.  Experimentation Strategies 9.  Open Innovation 10.  Diffusion and Adoption of Innovation 11.  Guest Lecture 12.  Diffusion and Adoption of Information Systems 13.  Guest Lecture 14.  Business Planning and Writing

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 3  

Knowledge = Justified True Belief (Plato)

“Knowledge is the perception of the a g r e e m e n t o r disagreement of two ideas.” (Locke, 1689)

“Knowledge is information that changes something or somebody — either by becoming grounds for actions, or by making an individual (or an institution) capable of d i f f e r e n t o r m o r e e f f e c t i v e action.” (Drucker, 2003)

“Knowledge is a justified personal belief that increases an individual’s capacity to take effective action.” (Alavi & Leidner, 1999)

Personification of knowledge (Greek Επιστηµη, Episteme) in Celsus Library in Ephesus, Turkey

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 4  

Brainteaser

•  Do you know how to tie a tie? •  Please, write it down.

5 Minutes

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 5  

Pragmatic Classification of Knowledge

Tacit Knowledge Implicit Knowledge Explicit Knowledge

Genes, feelings, subconscious knowledge „we can know more than we can tell“ (Polanyi, 1966)

Rational knowledge that can be explicated in principle, dogmas, social knowledge, technical knowledge etc.

Knowledge that can be coded by information into (socially constructed) symbol systems, e.g., •  Process descriptions •  Consulting expertise •  Regulations and procedures •  Clinical study design

explication

learning

Realm of individual knowledge

Realm of shared knowledge

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 6  

Knowledge Trends

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 7  

Brainteaser

•  Imagine, you are working in a students consulting project. The task of your project team of three people is the creation of a social media strategy for the Daimler AG.

10 Minutes

•  After four weeks of working in the project, you get a new team member.

•  What does she has to learn about the project for getting „on board“? How do you transfer your knowledge to her?

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 8  

In-house Problems in Handling Knowledge

•  Redundant research activities and project work

•  Low information quality in reports and analyses

•  Intransparency on knowledge resources

•  Limited documentation of project insights

•  Isolated knowledge domains

Example Despite of network character of company consisting of app. 650 branches in Germany, Fielmann has no joint network and storage of customer data

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 9  

What is Knowledge Management?

“Beginning in the mid 1990s, individuals and organizations began to think seriously about managing what they know. This movement came to be known as ‘knowledge management’.” (Davenport & Völpel, 2001, p. 212)

Knowledge management takes care that resource knowledge is … •  Delivered at the right time •  Available at the right place •  Present in the right shape •  Satisfying the quality requirements •  Obtained at lowest possible costs

Information •  Building vast amounts of

data into usable form •  Avoiding overloading

users with unnecessary data •  Eliminating wrong/old data •  Keeping information up to

date

Management •  Change management implications --

getting individuals to volunteer knowledge; getting business units to share knowledge

•  Demonstrating business value •  Bringing together people from various

units •  Determining responsibility for managing

knowledge

Technology •  Determining infrastructure

requirements •  Keeping up with new

technologies •  Security of data on Internet

(Alavi & Leidner, 1999)

Key concerns of knowledge management

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 10  

Key Concepts in Knowledge Management

Tacit vs. explicit knowledge Both types are important; Western firms focus largely on managing explicit knowledge

When is knowledge irrelevant? •  No need to exploit knowledge •  No production factor available for combining with knowledge

for creating products/processes •  No combination procedures known for specific production

factor •  Combination of knowledge and production factor not cost-

effective (Brockhoff, 2011)

Codification vs. personalization •  Codification approaches – repositories

of explicit knowledge to transfer knowledge

•  Personalization approaches – direct interaction between people for transferring knowledge

Knowledge markets •  Each organization = knowledge

market; knowledge is exchanged for things of value; e.g., money, respect, other knowledge

Intangible assets •  Translation of value of

knowledge into monetary value

•  Knowledge = intangible asset; never seen on balance sheets

(Davenport & Völpel, 2001)

Communities of Practice •  Idea developed in “organizational learning”

movement •  Knowledge flows best through networks of

people who have same work interests but are not in the same part of the organization

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 11  

Example of Knowledge Management

Chrysler – „Tech Clubs“ •  Motivation: Chrysler seriously addressed knowledge management on mid-1990s –

Quality problems in vehicle design previously been solved re-appeared •  Reason: Engineering experts spent most of their time on cross-functional teams

with people from other business functions – they were not able to pass along problems solved and lessons learned to each other

•  Solution: Chrylser formed collection of „Tech Clubs“ (knowledge-based communities) for technical specialists in many different areas, e.g., experts in car bumper technology got together to share knowledge; each club supported by facilitator and a Lotus Notes „book of knowledge“

•  Quality problems decreases •  After merging of Daimler Benz and Chrysler: adoption of „Tech Club“ approach

througout company

(Davenport & Völpel, 2001)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 12  

Knowledge Management Process

Feedback

R E F L E C T

identify   improvementsplan  changes

AC T

implement  changesmonitor  improvements

C ONC E P TUAL IZE

identify  knowledgeanalyz e  s trength/

weaknes s es

(Davenport & Völpel, 2001)

(Schreiber et al., 1999)

•  Inventarization of knowledge and organizational context

•  Analysis of strong and weak points – value of knowledge

•  Opportunity analysis concerning knowledge

•  e.g., form or quality of knowledge

•  Interventions concerning management, human resources and culture, e.g., recruitment

•  Organizational structure, e.g., teams with overlapping knowledge areas

•  (Technological) tools, e.g., intranet with knowledge profiling

CommonKADS knowledge management cycle

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 13  

Components of Knowledge Management

Knowledge Acquisition

Knowledge Identification

Knowledge Preservation

Knowledge Usage

Knowledge Distribution

Knowledge Development

(Probst et al., 1997)

Knowledge Goals

Knowledge Evaluation

Feedback

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 14  

Intellectual Capital Statement

•  Intellectual capital statement = strategic perspective on knowledge as intangible asset in company (knowledge management = operative perspective; execution of strategies of intellectual capital statement)

•  Classification of knowledge in intellectual capital statement •  Human capital – knowledge and skills of employees, e.g., chemical knowledge •  Structural capital – organization, technology and communication structure of

company, e.g., internal business processes •  Relational capital – relations to national and international customers and

partner, e.g., cooperation

•  Example: Skandia Navigator = intellectual capital navigator by Skandia insurance (Edvinsson,1997)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 15  

Sources of Knowledge

Combination of internal and external knowledge •  Traditional approach: in-house R&D develops

internal relevant knowledge •  But, relevant knowledge also developed

externally – internal knowledge important as: o  Means for estimating relevance of external

knowledge o  Entrance card to knowledge network

(Rosenberg, 1990)

•  Optimal combination of internal and external knowledge enables o  High external knowledge absorption and in-

house R&D = attractive for creative employees – war for talents

o  Low knowledge transfer costs

Example: Toolkits for user innovation •  Manufacturers abandon attempt to

understand user needs in detail in favor of transferring need-related aspects of product and service development to users (von Hippel, 2002)

(Brockhoff, 2011)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 16  

Sources of Knowledge

Combination of internal and external knowledge

Part of external knowledge regarding intellectual capital of company Amount of acquired external knowledge Effort in creating internal knowledge Size of internal knowledge base Amount of both knowledge types

External knowledge more cost-effective, but internally created knowledge lowers transfer costs for gaining external knowledge

     

     

(Brockhoff, 2011)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 17  

Sources of Knowledge

Combination of internal and competitor knowledge •  Legal competitor knowledge, e.g., technological

competitor analysis (e.g., TNS TRI*M competitor analysis), patent analysis

•  Sharing knowledge with competitors for generating market success

Combination of technological and marketing knowledge •  Marginal productivity of technological knowledge 2-3

times higher as marketing knowledge (based on Cobb-Douglas production function) – i.e. higher effort for generating technological knowledge justified

•  Uncertainties concerning technological knowledge easier to reduce as uncertainties concerning target markets

•  Example: combining knowledge of integrating NFC technology into smart phone with knowledge about intended customers and their usage behavior

(Brockhoff, 2011)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 18  

Brainteaser

•  Imagine, you are working in an IT Consultancy. Currently, your task is the development of a financial software.

•  To reduce costs, you decide to outsource this task to an Indian software company.

•  What are the challenges upcoming with your decision?

5 Minutes

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 19  

Knowledge Networks

(Maass, 2009)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 20  

Costs of Transferring Knowledge in Knowledge Networks

•  New knowledge has to be gained and integrated into existing knowledge areas before using it – transfer costs depend on five factors (Teece, 1977)

1.  Codification of knowledge 2.  Opportunity to teach somebody on this knowledge 3.  Complexity of knowledge (the more complex the knowledge the more effort is needed to

transfer knowledge) 4.  Generality of knowledge (age of knowledge when transferring) 5.  Experience of involved actors (number of executed transfers)

•  “Technology transfer costs are therefore defined as the costs of transmitting and absorbing all of the relevant unembodied knowledge. The costs of performing the various activities which have to be conducted to ensure the transfer of the necessary technological know-how will represent the cost of technology transfer.” (Teece, 1977, p. 245)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 21  

Costs of Transferring Knowledge in Knowledge Networks

•  Four groups of transfer costs: 1)  Costs of pre-engineering (basic characteristics of technology are revealed to transferee) 2)  Engineering costs while transferring process/product design and process/product

engineering 3)  Costs of R&D personnel during whole transfer 4)  Pre-start-up training costs and learning/debugging costs while start-up

•  Study concerning transferring manufacturing knowledge from one country to firms in another country (Teece, 1977); 26 multinational projects considered

•  Implications: o  Transfer costs average 19% of total project costs o  Success of more experienced enterprises (indicated by lower transfer costs) o  Transfer costs are decreasing cost activities (decline with each application of given

innovation) o  Manufacturing experience is important aspect, but not size of company or R&D to sales ratio

– super giant firms seem to have no advantage over moderately sized firms

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 22  

How to Organize?

•  “A key aspect of the management of knowledge in organizations is the development of an organizational structure to perform knowledge-oriented tasks.” (Davenport & Völpel, 2001, p. 215)

•  Organizational structure has at least three levels: ①  Chief Knowledge Officer (CKO) at senior, and visible, level ②  Cadre of knowledge project managers (middle management) ③  Knowledge managers doing day-to-day work of knowledge, e.g.,

creating and editing knowledge objects in a repository

•  Technologies for knowledge management •  Repository and access technologies, e.g., intranets, search engines •  Structured knowledge representation tools for using knowledge in real-

time applications; e.g., rule-based/case-based systems, semantic representations

•  Knowledge management e-commerce tools for distributing knowledge in knowledge networks

(Davenport & Völpel, 2001)

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 23  

Types of Knowledge Management Projects

①  Repositories •  Objective: implementing knowledge repository for capturing knowledge for later and broader

access by others in the same organization, e.g. best practices, sales knowledge ②  Asset Management

•  Objective: better management of knowledge assets, either measuring their level or value within an organization

(Davenport & Völpel, 2001)

③  Transfer •  Objective: knowledge transfer through technological means or direct contact between people

④  Environment •  Objective: improving overall environment for managing knowledge in projects, e.g., increasing

awareness of knowledge and its role in business

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 24  

Improving Effectiveness of Knowledge Management

•  Incentive systems and mentoring programs •  Appointing “process champions” enabling comprehensive

knowledge sharing processes •  Executive management declarations on expectations of trust and

openness in knowledge creation and management

•  Transfer of tacit knowledge by debriefing after significant events; e.g., conferences, seminars; meeting with important clients or vendors meetings

•  Using a variety of communication formats for both tacit and explicit knowledge

•  Providing systems specifically for project knowledge management

•  Seeding component organizations in networks with highly regarded and knowledgeable members from other organizations

(Von Krogh, 1998; Geisler, 1999)

Intra-Organizational

Structures

Codification of Knowledge

Inter-Organizational

Structures

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 25  

Lecture Agenda

Innovation Management 1.  Introduction 2.  Knowledge Management 3.  Strategic Innovation Management 4.  Guest Lecture 5.  New Product Development 6.  Creativity Techniques 7.  Planning Product Features 8.  Experimentation Strategies 9.  Open Innovation 10.  Diffusion and Adoption of Innovation 11.  Guest Lecture 12.  Diffusion and Adoption of Information Systems 13.  Guest Lecture 14.  Business Planning and Writing

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

25.04.12 Slide 26  

Literature

Books: •  Albers, S. & Gassmann, O. (2011), Handbuch Technologie- und Innovationsmanagement, Gabler Verlag. •  Drucker, P. (2003), The New Realities, Transaction Publishers. •  Locke, J. (1690), An Essay Concerning Human Understanding - Book IV Of Knowledge and Probability, Hayes & Zell. •  Polanyi, M. (1966), The tacit dimension, Garden City, Doubleday. •  Schreiber, G.; Akkermans, H.; Anjewierden, A.; de Hoog, R.; Shadbolt, N.; de Velde, W. V. & Wielinga, B. (1999), Knowledge

Engineering and Management - The CommonKADS methodology, The MIT Press.

Papers: •  Alavi, M. & Leidner, D. E. (1999), 'KNOWLEDGE MANAGEMENT SYSTEMS: ISSUES, CHALLENGES, AND BENEFITS',

Communications of AIS 1, 1-37. •  Brockhoff, K. (2011), Management des Wissens als Hauptaufgabe des Technologie- und Innovationsmanagements, in Sönke

Albers & Oliver Gassmann, ed., 'Handbuch Technologie- und Innovationsmanagement', Gabler. •  Davenport, T. H. & Völpel, S. C. (2001), 'The rise of knowledge towards attention management', Journal of Knowledge

Management 5(3), 212-221. •  Edvinsson, L. (1997), 'Developing intellectual capital at Skandia', Long Range Planning 30(3), 366-373. •  von Hippel, E. & Katz, R. (2002), 'Shifting Innovation to Users via Toolkits', Management Science 48(7), 821-833. •  Maass, W. (2009), 'Elektronische Wissensmärkte: Handel von Information und Wissen über digitale Netze (Habilitationsschrift

Universität St. Gallen)’. •  Probst, G.; Raub, S.; Romhardt, K.: Wissen managen. FAZ/Gabler, Wiesbaden und NZZ/Gabler, Zürich, 1997. •  Rosenberg, N. (1990), 'Why do firms do basic research (with their own money)?', Research Policy 19, 165-174. •  Teece, D. J. (1977), 'Technology Transfer by Multinational Firms: The Resource Cost of Transferring Technological Know-How',

The Economic Journal 87(346), 242-261.

Univ.-Prof. Dr.-Ing. Wolfgang Maass  

Univ.-Prof. Dr.-Ing. Wolfgang Maass Chair in Information and Service Systems Saarland University, Germany